14394 results for ""Pennsylvania+German"+ACS+study+'Socius'+open+access"

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• Gene expression from human iPSC derived motor neurons.

  Gene expression from human iPSC derived motor neurons.

  Study EGAS00001003785

• BAP1_sequence_of_uveal_melanoma_cell_lines

  Detection of BAP1 mutations in DNA from 3 uveal melanoma cell lines.

  Study EGAS00001001520

• Low_input_LC__ISC_

  R&D project to develop low input library construction methods.

  Study EGAS00001001856

• Somatic_mutation_in_edited_cholangiocyte_organoids_WGS

  Characterisation of mutation rates and patterns in edited human cholangiocyte organoids (WGS)

  Study EGAS00001006326

• Chugai_colorectal_organoid_sequencing

  Genomic and transcriptomic characterization of drug-resistant colon cancer stem cell lines.

  Study EGAS00001000872

• Transcriptomic profiling of lymphedema

  RNA-seq of skin from human subjects with and without lymphedema

  Study EGAS00001004516

• Psoriatic_arthritis_WGS

  Whole genome sequencing of immune cells from patients diagnosed with psoriatic arthritis

  Study EGAS00001002822

• Infant_Spindle_Tumour_Study

  We aim to describe the transcriptomic landscape of infant spindle cell tumours.

  Study EGAS00001002935

• Plasma DNA profile in DNASE1L3 deficiency-Mouse AAV samples

  Plasma DNA profile in DNASE1L3 deficiency-Mouse AAV

  Study EGAS00001004409

• PBMC_dual_10X_kit

  Dual snRNAseq and ATACseq of replicate PBMC samples for 10X beta testing.

  Study EGAS00001004834

• Genomic analyses to identify metabolic vulnerabilities

  Genomic analyses to identify metabolic vulnerabilities on PDX samples

  Study EGAS00001007244

• Settlement of Polynesia

  Genotypes used to reconstruct the settlement timings and paths of Polynesia.

  Study EGAS00001005362

• HCA_Muscle_Adult_Wellcome_RNA_Managed_Access

  Transcriptomic analysis of skeletal muscle, to understand the mechanisms of muscle ageing.

  Study EGAS00001007495

• Reference epigenome ADMSC07 h3k4me1 ChIP-Seq data generated from KEP study

  ADMSC07 h3k4me1 ChIP-Seq paired end data

  Dataset EGAD00001007391

• CONTAGIOUS trial - COVID-19 16S metadata

  Study metadata, containing the clinical information on samples and patients

  Dataset EGAD00001008006

• Carcinoid study - WES dataset

  Fernandez-Cuesta et al, 2014, Nature Communication, Whole exome sequencing data set

  Dataset EGAD00001000820

• MPNST exome and genome

  This is the complete dataset (exome and genome) for the EGAS00001000974 study.

  Dataset EGAD00001001040

• Reference epigenome IPS06_X_ENeuron_WGBS data generated from KEP study

  A IPS06_X_ENeuron_WGBS paired end data for Early neuron cells(Tuj1)

  Dataset EGAD00001003478

• Reference epigenome OB56_N_PreA_mRNA-Seq data generated from KEP study

  A OB56_N_PreA_mRNA-Seq paired end data for Preadipocytes(fat)

  Dataset EGAD00001003486

• Reference epigenome IPS05_X_NPC_WGBS data generated from KEP study

  A IPS05_X_NPC_WGBS paired end data for Neural progenitor cells(Nestin)

  Dataset EGAD00001003477

• National Institute on Aging (NIA) Long Life Family Study (LLFS)

  The Long Life Family Study (LLFS) is an international collaborative study of the genetics and familial components of exceptional survival, longevity, and healthy aging. Families were recruited through elderly probands (generally in their 90s) who self-reported on the survival history of their parents and siblings, and on the basis of this information, families which showed clustering of exceptional survival were recruited. [Specifically, a Family Longevity Selection Score (FLOSS) ≥7 was required. The FLOSS measures the average excess Observed lifespan over that Expected based upon lifetables, while adding a bonus term for still-living individuals. Thus FLOSS is a useful tool for scoring and selecting families for inclusion in a research study of exceptional survival (Sebastiani et al., 2009, PMID: 19910380)]. Probands resided in the catchment areas of four Field Centers (Boston University, Columbia University, University of Pittsburgh, and University of Southern Denmark). Recruited family members were phenotyped through extensive in-home visits by teams of technicians who traveled all over the USA and Denmark. Blood assays were centrally processed at a Laboratory Core (University of Minnesota) and protocols were standardized, monitored and coordinated through a Data Management Coordinating Center (Washington University). We examined and extensively phenotyped in all major domains of healthy aging, 4,953 individuals in 539 families through comprehensive in-home visits. Of these, 4,815 gave dbGaP sharing permission and had sufficient quantity/quality of DNA for GWAS genotyping. This large collection of families, selected on the basis of clustering for exceptional survival, is a unique resource for the study of human longevity and healthy aging. We estimate that less than 1% of the Framingham Heart Study (FHS) families (a roughly random population family sample) would meet the minimal entrance criteria for exceptional survival required in the LLFS (Sebastiani et al., 2009, PMID: 19910380). Thus, the least exceptional LLFS families show more clustering for exceptional longevity than 99% of the FHS families. Although the LLFS pedigrees were selected on the basis of longevity per se in the upper generation (and the generation above that), the children's generation have significantly lower rates of many major diseases and have better healthy aging profiles for many disease phenotypes (Newman et al., 2011, PMID: 21258136). The participants had their first in-person visit between 2006 and 2009. After that visit, they were contacted annually by telephone to update vital status, medical history, and general health. Between 2014 and 2017, willing participants completed a second in-person visit. The second visit followed the same protocols and centralized training as the first visit. During the second visit, a portable carotid ultrasound exam was added. Again, participants were continuously contacted annually for telephone follow-up during the period of the second in-person visit and after that. Annual telephone follow-ups currently ongoing, and plans for a third in-person visit are in progress.

  Study phs000397

• Genome-Wide Association of Type 2 Diabetes in Africans: The AADM Study

  The Africa America Diabetes Mellitus (AADM) study is a genetic epidemiological study of type 2 diabetes in Sub-Saharan Africa. Study participants were enrolled through university medical centers in Nigeria, Ghana, and Kenya. Ethical approval for the study was obtained from the Institutional Review Board (IRB) of each participating institution. All subjects provided written informed consent for the collection of samples and subsequent analysis. The case definition of type 2 diabetes was based on the American Diabetes Association (ADA) criteria. After providing informed consent, participants underwent the same enrollment procedures, which included collection of demographic information, medical history, clinical examination and a blood draw. Genome-wide SNP genotyping was done on either the Axiom™ PanAFR SNP array (n=1,808) or the Multi-Ethnic Global Array (MEGA) (n=3,423). After appropriate quality control, in silico imputation was done using the African Genome Resources Haplotype Reference Panel (at the Sanger Imputation Service). Imputed genotypes were filtered for variants with minor allele frequency (MAF)≥ 0.01 and information score (info) ≥ 0.3 for genetic association analysis. Genome-wide association analysis between type 2 diabetes and the imputed genotype dosages was done using a generalized linear mixed model, which adjusted for age, gender, body mass index, the genetic relatedness matrix and the first three principal components (PCs) of the genotypes.Metabolomics profiling of plasma samples of type 2 diabetes (T2D) cases and controls in Nigerians (West Africa) was done in the AADM Study. Plasma metabolites were measured in a total of 580 individuals (N=310 for the discovery phase and N=270 for the replication stage) using the global/untargeted approach on the Metabolon platform and following the manufacturer's standard operation protocols. The analytic methods are described in detail in Doumatey et al. [Genome Med 2024]. The measured metabolites level represented by peak areas are relative values. The peak area data were batch-normalized to remove the instrument batch effects (batch variability) and the batch-normalized data correspond to the median-scaled raw data. For each identified metabolite, the minimum value across all batches in the batch-normalized was imputed for the missing values. The batch-normalized and imputed data are natural log-transformed and consist of 1116 metabolites for the discovery cohort and 1071 metabolites for the replication. Welch's two-sample t-test on the log-transformed data was used to identify metabolites differentially expressed between T2D cases and controls . All other statistical analyses conducted on both the replication and discovery cohorts used the log-transformed data. To merge the discovery and replication, the same quality control samples (bridge samples) were run with each batch of the experimental samples in both cohorts and used to correct for additional variability and uniformize the procedures. The resulting merged data is the QC-normalized and imputed data that contains only metabolites that were common to both cohorts and successfully bridged for all batches (n= 891 metabolites).

  Study phs001844

• Pharmacological improvement of CFTR function rescues airway epithelial homeostasis and host defense in children with cystic fibrosis

  This dataset encompasses single-cell RNA sequencing data derived from nasal swabs of a paired cohort of school-aged children with cystic fibrosis. The study includes samples both before (n=13) and after initiation (n=13) of elexacaftor/tezacaftor/ivacaftor (ETI) treatment. Additionally, age- and sex-matched controls were included (n=12). Detailed information about the study design and methodology can be found in the manuscript: “Pharmacological improvement of CFTR function rescues airway epithelial homeostasis and host defense in children with cystic fibrosis”.

  Dataset EGAD50000000173

• De novo detection of somatic variants

  The Tumor Profiler Study is an observational trial combining a prospective diagnostic approach to assess the relevance of in-depth tumor profiling to support clinical decision-making with an exploratory approach to improve the biological understanding of the disease. This dataset contains scDNA-seq data for 3 ovarian cancer samples from the Tumor Profiler Study used to validate LongSom. LongSom is a computational workflow leveraging high-quality long-read scRNA-seq data to call de novo somatic single-nucleotide variants (SNVs), including in mitochondria (mtSNVs), copy-number alterations (CNAs), and gene fusions, to reconstruct tumor clonal heterogeneity.

  Dataset EGAD50000001292

• Study of biomarkers implicated in radio-immunotherapy response in metastatic cancer

  Immuno-radiotherapy may improve outcomes for patients with advanced solid tumors, although optimized combination modalities remain unclear. Here, we report the analysis from the SABR-PDL1 (NCT02992912) trial that evaluated the PD-L1 inhibitor atezolizumab in combination with stereotactic body radiation therapy (SBRT) in patients with advanced cancer.

  Study EGAS50000000681

• Study of biomarkers implicated in radio-immunotherapy response in metastatic cancer

  Immuno-radiotherapy may improve outcomes for patients with advanced solid tumors, although optimized combination modalities remain unclear. Here, we report the analysis from the SABR-PDL1 (NCT02992912) trial that evaluated the PD-L1 inhibitor atezolizumab in combination with stereotactic body radiation therapy (SBRT) in patients with advanced cancer.

  Study EGAS50000001149

• Transcriptomic data from a SARS-CoV-2 human challenge study (Kelly Research Group, Arkansas Children’s Research Institute)

  This dataset contains paired-end RNA-Seq data generated from mid-turbinate nasal and throat samples collected as part of a first-in-human SARS-CoV-2 experimental challenge study conducted in the United Kingdom in 2021. Total RNA was extracted using QIAamp Viral RNA kits (Qiagen), and libraries were prepared using TruSeq RNA Exome kits (Illumina). Sequencing was performed on a NovaSeq X Plus instrument configured for 100 bp paired-end reads. The dataset includes raw FASTQ files and associated de-identified metadata.

  Dataset EGAD50000002078

• Single-cell RNA-seq data from metastatic ovarian cancer for quality control study

  Quality control is a crucial preliminary step in any single-cell RNAseq experiment, where hard thresholds are commonly used. In order to develop a methodology for a more precise cell filtering in the early steps of a scRNAseq data analysis, we collected tissue samples before chemotherapy from 4 patients.

  Study EGAS00001005066

• Exome Sequencing to Identify Causes of Leukaemia Predisposing Congenital Neutropenias (2019-08-19)

  The objective of this study is to identify the causative genes in two unrelated congenital neutropenia families. We aim to whole exome sequence the affected individuals, unaffected siblings and parents in both cases in an effort to idenitfy the causative genetic mutation. Exome capture will be performed using Agilent SureSelect system. Subsequently, exome libraries will sequenced using the Illumina HiSeq platform. Sequence variant calling will be done in house and common variants excluded using public databases and data from unaffected family members. . This dataset contains all the data available for this study on 2019-08-19.

  Dataset EGAD00001005264

• MutWP5: CRUK Mutographs of Cancer: BRCA Carriers (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastecomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010112

• RNA and ChIP Sequencing datasets from the study Kalirin-RAC controls nucleokinetic migration in ADRN-type neuroblastoma

  This dataset contains the RNA and ChIP Sequencing data from the study Kalirin-RAC controls nucleokinetic migration in ADRN-type neuroblastoma. The data is organized in 7 experiments which are divided by both sequencing technology or the application of siRNA or drug interventions (or lack thereof) on neuroblastoma cell lines. The experiment names and the file names have been chosen in each respective experiment to guide future users of the data to replicate the analyses in the manuscript.

  Dataset EGAD00001006964

• MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (Exome)

  Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequently be sent for whole-genome sequencing. Results from this portion of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010110

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015710

• Sequence data for study: Mobilization of tissue-resident memory CD4+ T lymphocytes from bone marrow and their contribution to a systemic secondary immune reaction

  Short Description: This study contains 7 RRBS samples, including 3 ex vivo CD4+ Trm (2 x spleen and 1 x bone marrow) and 4 blood tetanus (TT) and measles (Me) antigen-reactive memory CD4+ cells before and one day post DTaP (diphtheria-tetanus-pertussis) and MMR (measles-mumps-rubella) vaccination, respectively (1 x tetanus D0, 1 x tetanus D1, 1 x measles D0, 1 x measles D1). Technology: Illumina HiSeq 2500 Filetype: fastq format

  Dataset EGAD00001007886

• MutWP5: CRUK Mutographs of Cancer: BRCA Carriers (Exome)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 20 women who underwent risk-reducing reduction mastecomies due to germline BRCA1/2. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who had cosmetic breast reduction surgeries and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010115

• Single-cell RNA-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell RNA sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015717

• Investigating the genetics of immunity against Salmonella in humans (2019-09-05)

  This study entails whole genome sequencing of an interleukin (IL)-12 b-1 receptor-deficient individual who presented with a chronic systemic Salmonella Enteritidis infection that did not resolve with standard IFNg and antibiotic treatment. Whole genome sequencing of the patient's parents are also included. This data is part of a pre-publication release. For information on the proper use of pre-publication data shared by the Wellcome Trust Sanger Institute (including details of any publication moratoria), please see http://www.sanger.ac.uk/datasharing/ . This dataset contains all the data available for this study on 2019-09-05.

  Dataset EGAD00001005311

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015711

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015719

• MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (WG)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010113

• Single-cell ATAC-sequencing of rhabdomyosarcoma tumour tissue (2025-09-30)

  This study investigates high-risk rhabdomyosarcoma (RMS) using multiple single-cell and spatial genomic technologies. We generated and analysed single-cell and single-nucleus RNA-sequencing, chromatin accessibility, and spatial transcriptomics data from primary tumours and validation samples. These datasets characterise cellular diversity within rhabdomyosarcoma and identify cell states associated with aggressive disease. The data support research into tumour biology, risk stratification, and therapeutic target discovery. This repository houses the single-cell ATAC sequencing of RMS tumours data. . This dataset contains all the data available for this study on 2025-09-30.

  Dataset EGAD00001015715

• MutWP5: CRUK Mutographs of Cancer: Breast: Reduction Mammoplasty (Exome)(Novaseq)

  Sequencing of LCM-derived microbiopsies from 10 women who underwent reduction mammoplasty. Goal to assess the mutational burden, spectrum, and clonal dynamics within the tissue. Exome data will be used as a driver and clonality screen, highly clonal or driver-containing samples will subsequenctly be sent for whole-genome sequencing. Results from this poriton of the study will be compared to women who are BRCA1/2 germline carriers and those with cancer. . This dataset contains all the data available for this study on 2023-03-08.

  Dataset EGAD00001010116

• Comprehensive copy number aberration analysis using digital Multiplex Ligation-dependent Probe Amplification (digitalMLPA) in pediatric B-cell precursor acute lymphoblastic leukemia

  In this study a next-generation sequencing based method was applied to comprehensively screen for recurrent, disease-relevant copy number aberrations in a cohort of Hungarian patients. Diagnostic bone marrow samples from 260 children with B-cell acute lymphoblastic leukemia as well as 72 control samples and were investigated by digital multiplex ligation-dependent probe amplification using the disease-specific D007 probemix. Whole chromosome gains and losses, as well as subchromosomal copy number aberrations were simultaneously profiled.

  Dataset EGAD00001010878

• Phenotypic and Genotypic Study of Keratoconus

  Keratoconus, a disease in which the cornea is abnormally steep and thin, affects approximately 1 in 2000 individuals and usually begins in the second decade of life. Keratoconus is a progressive disorder that results in loss of vision that cannot be alleviated by contact lenses or glasses alone and is a leading indication for corneal transplantation in developed countries (Udar et al., 2006, PMID: 16877401). Keratoconus has a strong genetic component, and while several causative genes are clearly suspected, the underlying pathogenic processes have not yet been identified. The goal of our research is to identify genes that harbor mutations contributing to keratoconus and underlying biochemical processes relevant to keratoconus pathogenesis and to develop a better understanding of the etiology of keratoconus, leading to improved detection, treatment, and management. We will enroll isolated keratoconus along with familial cases and unaffected relatives when available. The subject population will consist of individuals diagnosed with keratoconus and unaffected relatives in families. Individuals/families will be ascertained through support groups and clinical collaborators. The identities of the study participants will be known only to Dr. Chakravarti, the study coordinator, physicians in the team and the post-doctoral fellow(s) working directly on the project. DNA, lymphocytes, and lymphoblastoid cell lines may be prepared from the blood samples for future use. Molecular analyses using markers and sequencing and statistical analyses of these data will be used to identify regions of human chromosomes where putative keratoconus disease genes reside. Analyses of coding DNA sequences within genes from keratoconus subjects will be compared to published control sequences to identify disease specific variants. Additionally, to understand disease pathogenesis, subsets of patients may be asked to provide tear samples. Study subjects will not directly benefit from participation and results will not be disclosed to participants nor their health care providers, unless medically relevant.

  Study phs003168

• A Genome-Wide Association Study of Lung Cancer Risk

  Three genetic loci for lung cancer risk have been identified by genome-wide association studies (GWAS), but inherited susceptibility to specific histologic types of lung cancer is not well established. We conducted a GWAS of lung cancer and its major histologic types genotyping 515,922 single nucleotide polymorphisms (SNPs) in 5,739 incident lung cancer cases and 5,848 controls from one population-based case-control study and three cohort studies. Results were combined with summary data from 10 additional studies for a total of 13,300 cases and 19,666 controls of European descent. Four studies also provided histology data for replication resulting in 3,333 adenocarcinomas (AD), 2,589 squamous cell carcinomas (SQ), and 1,418 small cell carcinomas (SC). In analyses by histology, rs2736100 (TERT) on chromosome 5p15.33, was associated with risk of adenocarcinoma (OR=1.23, 95%CI=1.13-1.33, P=3.02x10-7), but not other histologic types (OR=1.01, P=0.84, and OR=1.00, P=0.93, for SQ and SC, respectively). This finding was confirmed in each replication study and overall meta-analysis (OR=1.24, 95%CI=1.17-1.31, P=3.74x10-14 for AD and OR=0.99, P=0.69 and OR=0.97, P=0.48, for SQ and SC, respectively). Other previously reported association signals on 15q25 and 6p21 were also refined, but no additional loci reached genome-wide significance. In conclusion, a lung cancer GWAS identified a distinct hereditary contribution to adenocarcinoma. Note: The lung study dataset to be released to dbGaP and caBIG excludes 47 individuals from the PLCO cohort who consented to participate only in cancer research projects and 22 individuals because of updated QC. Thus, the released dataset is derived from 11517 subjects, 5699 cases and 5818 controls. After the updated QC, the dataset to be released to dbGaP and caBIG includes 506062 SNPs.

  Study phs000336

• The National Myelodysplastic Syndromes (MDS) Study

  Myelodysplastic syndromes (MDS) are the most common cause of adult bone marrow failure in the US and occur predominantly in people over the age of 60. Much of the morbidity and mortality for MDS is due to complications from low blood counts (e.g., infections and bleeding). MDS is caused by acquired DNA mutations that occur in a patient's blood cells as they grow older. Accumulating evidence suggests that MDS patients may traverse through a series of antecedent hematopoietic conditions defined by, i) clonal hematopoiesis (i.e., detectable somatic mutations in a person's blood cells) without low blood counts, a condition that affects up to 10% of individuals 70 years old and is termed Clonal Hematopoiesis of Indeterminate Potential (CHIP), or ii) clonal hematopoiesis with low blood counts (i.e., cytopenias) but no evidence of bone marrow dysplasia, termed Clonal Cytopenia of Undetermined Significance (CCUS). Nearly all CCUS patients will develop MDS over a ten year period, highlighting the prognostic importance of this disease. A better understanding of the genetic mutations, including non-coding and structural variants (SVs), occurring in CCUS and MDS could provide valuable insight into the natural history of MDS development. The NHLBI is conducting a longitudinal, observational study to create a standardized clinical dataset linked to a prospectively collected, consistently processed, and well-characterized biospecimen repository derived from approximately 1750 participants with suspected or newly diagnosed MDS or MDS/myeloproliferative neoplasm (MPN) overlap. These volunteers will donate biological specimens (like bone marrow and blood) and medical information, including details of their symptoms, how they perceive their quality of life, the treatments they receive, and what their doctor says about the severity of their illness over time. This information will be collected at pre-determined time points for the duration of the study. Study participants may be followed for life.

  Study phs002714

• A Genome-Wide Association Study of Peripheral Arterial Disease

  The Electronic Medical Record Phenotypes and Community-engaged Genomic Association Study aims to identify genetic variants mediating susceptibility to peripheral arterial disease (PAD). The study leverages a biorepository of blood samples of 1688 PAD cases and 1649 controls, and the electronic medical record (EMR) to annotate the biorepository. PAD cases were identified from the vascular laboratory database as having an ankle brachial index (ABI) <0.9 at rest or after exercise or having non-compressible vessels. Controls were without prior history of atherosclerotic vascular disease and when tested, no evidence of ischemia on a stress test. Phenotypes and environmental exposures including age, ethnicity, demographic and anthropometric data are derived from the Mayo Electronic Medical Record (EMR). Comorbidities were determined using algorithms for diabetes and hypertension based on ICD-9 codes and medication use. Relevant laboratory data, including lipid levels, fasting blood sugar and serum creatinine at index date or within a 1-year window of the index date were extracted. Medication classes at index date were identified using Mayo's Natural Language Processing-based system with RxNorm codification and NDF-RT terminologies mapping. Smoking status was confirmed by natural language processing of clinical notes. Genotyping of ~600,000 SNPs across the genome is being conducted at the Broad Institute using the Illumina 660W platform. Statistical analyses will be conducted to identify genetic variants associated with susceptibility to PAD.

  Study phs000203

• NIH Division of Intramural Research Multiomic Monogenic Disease Study

  This cross-sectional, observational study utilized high-dimensional approaches, including transcriptomic analysis, serum protein profiling, and peripheral blood frequency assessments, to compare 228 adult and pediatric patients diagnosed with 22 monogenic immune-mediated conditions impacting various key immunological pathways, with 42 age- and sex-matched healthy controls. Participants were enrolled in clinical protocols at the National Institutes of Health in Bethesda, Maryland, USA. The primary objectives of the study were twofold: first, to identify disease-specific and shared "pan-disease" signatures using the collected data, and second, to develop a Random Forest classifier integrating these datasets to differentiate between age- and sex-matched healthy individuals and monogenic patients. This classifier produced a metric known as the "Immune Health Metric" (IHM). Subsequent analysis demonstrated that the IHM effectively distinguished healthy subjects from individuals with multiple polygenic autoimmune and inflammatory diseases in independent datasets. Moreover, it exhibited correlations with healthy aging and tracked disease activities and treatment responses across both immunological and non-immunological conditions. Additionally, the IHM accurately predicted age-dependent antibody responses to various vaccines, including influenza, Hepatitis A/B, Yellow Fever, Varicella Zoster, and Meningococcal vaccines.The microarray-based transcriptomic data, aptamer-based serum protein concentrations (Somalogic platform), peripheral blood frequency data, and clinical information will be made accessible through the database of Genotypes and Phenotypes (dbGaP).

  Study phs002732

• A Perioperative Study of Safusidenib in Patients with IDH1-Mutated Glioma

  10 participants with a radiological or pathological diagnosis of WHO Grade 2 lower-grade glioma (LGG) were recruited at a single center starting in December, 2022. Eligibility criteria permitted participants who had undergone prior surgery for WHO Grade 2 LGG, but excluded those with a history of prior radiation or chemotherapy.In Part A of the study, participants underwent an initial craniotomy with tumor biopsy and a lumbar puncture for cerebrospinal fluid (CSF) collection at study entry. Following sample collection, participants received safusidenib at the recommended phase 2 doses of 250 mg twice daily (b.i.d.) for a period of 22–36 days. This was followed by a second craniotomy for maximal safe tumor resection and a repeat lumbar puncture within 5 hours of the final pre-resection dose of safusidenib. Tumor, blood, and CSF samples were collected at both surgical time points for comprehensive translational research.Molecular analyses were performed on samples collected at both time points. These included pharmacokinetics (PK), targeted metabolomics, whole-genome sequencing (WGS) of tumor tissue, single-nucleus RNA sequencing (snRNA-seq), and DNA methylation profiling on all patients. Targeted metabolomics was conducted on samples from 9 participants, while spatial transcriptomics and spatial metabolomics were performed on tumor tissue from 3 participants each. Histone methylation profiling was conducted on samples from 8 participants.

  Study phs003976

• Collaborative Cohort of Cohorts for COVID-19 Research (C4R): Coronary Artery Risk Development in Young Adults Study (CARDIA)

  Cohort Description The Coronary Artery Risk Development in Young Adults (CARDIA) study is a study examining the development and determinants of clinical and subclinical cardiovascular disease and their risk factors. It began in 1985-6 with a group of 5115 black and white men and women aged 18-30 years. The participants were selected so that there would be approximately the same number of people in subgroups of race, gender, education (high school or less and more than high school), and age (18-24 and 25-30 years) in each of 4 centers: Birmingham, AL; Chicago, IL; Minneapolis, MN; and Oakland, CA. These same participants were asked to participate in follow-up examinations during 1987-1988 (Year 2), 1990-1991 (Year 5), 1992-1993 (Year 7), 1995-1996 (Year 10), 2000-2001 (Year 15), 2005-2006 (Year 20), 2010-2011 (Year 25), 2015-2016 (Year 30), and 2021-2022 (Year 35). Data Being Submitted Wave 1 questionnaire data includes 397 variables for up to 2434 CARDIA participants in C4RWave 2 questionnaire data includes 448 variables for up to 1901 CARDIA participants in C4RDried Blood Spot/Serosurvey data includes 7 variables for up to 1332 CARDIA participants in C4RDerived data includes 43 variables for up to 2723 CARDIA participants in C4RPhenotype data includes 113 variables for up to 2723 CARDIA participants in C4R

  Study phs003045